64 lines
2.8 KiB
Python
64 lines
2.8 KiB
Python
from fastvideo import VideoGenerator
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from fastvideo.configs.sample import SamplingParam
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import os
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os.environ["FASTVIDEO_ATTENTION_BACKEND"] = "VIDEO_SPARSE_ATTN"
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OUTPUT_PATH = "video_samples"
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def main():
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# FastVideo will automatically use the optimal default arguments for the
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# model.
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# If a local path is provided, FastVideo will make a best effort
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# attempt to identify the optimal arguments.
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model_name = "FastVideo/FastWan2.1-T2V-14B-Diffusers"
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generator = VideoGenerator.from_pretrained(
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model_name,
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# FastVideo will automatically handle distributed setup
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num_gpus=1,
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use_fsdp_inference=True,
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dit_cpu_offload=False,
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vae_cpu_offload=False,
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text_encoder_cpu_offload=False,
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# Set pin_cpu_memory to false if CPU RAM is limited and there're no frequent CPU-GPU transfer
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pin_cpu_memory=True,
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# image_encoder_cpu_offload=False,
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)
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sampling_param = SamplingParam.from_pretrained(model_name)
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# sampling_param.image_path = "test.jpg"
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# sampling_param.num_inference_steps = 0
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# Generate videos with the same simple API, regardless of GPU count
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i2v_prompt = "An astronaut hatching from an egg, on the surface of the moon, the darkness and depth of space realised in the background. High quality, ultrarealistic detail and breath-taking movie-like camera shot."
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i2v_prompt = "A little girl is packing a suitcase and the contents starts flying out of the suitcase everywhere."
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prompt = i2v_prompt
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# prompt = (
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# "A curious raccoon peers through a vibrant field of yellow sunflowers, its eyes "
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# "wide with interest. The playful yet serene atmosphere is complemented by soft "
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# "natural light filtering through the petals. Mid-shot, warm and cheerful tones."
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# )
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results = generator.generate_video(prompt, output_path=OUTPUT_PATH, save_video=True, sampling_param=sampling_param)
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stage_names = results["stage_names"]
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stage_execution_times = results["stage_execution_times"]
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# print(logging_info)
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print(stage_names)
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print(stage_execution_times)
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# video = generator.generate_video(prompt, sampling_param=sampling_param, output_path="wan_t2v_videos/")
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return
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# Generate another video with a different prompt, without reloading the
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# model!
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prompt2 = (
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"A majestic lion strides across the golden savanna, its powerful frame "
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"glistening under the warm afternoon sun. The tall grass ripples gently in "
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"the breeze, enhancing the lion's commanding presence. The tone is vibrant, "
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"embodying the raw energy of the wild. Low angle, steady tracking shot, "
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"cinematic.")
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video2 = generator.generate_video(prompt2, output_path=OUTPUT_PATH, save_video=True)
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if __name__ == "__main__":
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main()
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